Clusteval logo ClustEval clustering evaluation framework

Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 1.0 metric=euclidean
k=74
samples=20
Clustering
Self Organizing Maps 1.0 x=150
y=142
Clustering
Spectral Clustering 1.0 k=18 Clustering
clusterdp 1.0 k=11
dc=3.785665920228867
Clustering
HDBSCAN 1.0 minPts=4
k=83
Clustering
AGNES 1.0 method=single
metric=euclidean
k=16
Clustering
c-Means 1.0 k=52
m=5.0
Clustering
k-Medoids (PAM) 1.0 k=25 Clustering
DIANA 1.0 metric=euclidean
k=154
Clustering
DBSCAN 1.0 eps=3.0024246953539295
MinPts=208
Clustering
Hierarchical Clustering 1.0 method=single
k=190
Clustering
fanny 1.0 k=42
membexp=2.0
Clustering
k-Means 1.0 k=230
nstart=10
Clustering
DensityCut 1.0 alpha=0.9
K=5
Clustering
clusterONE 0.0 s=34
d=0.36666666666666664
Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=3.9162061243746904
maxits=2000
convits=350
Clustering
Markov Clustering 0.0 I=4.298298298298298 Clustering
Transitivity Clustering 1.0 T=2.8264110267008524 Clustering
MCODE 0.999 v=0.9
cutoff=3.589855614010133
haircut=F
fluff=F
Clustering